


[Fandom stats] Gender bias in television

by toastystats (destinationtoast)



Series: Fandom Stats [57]
Category: Fandom - Fandom
Genre: Cross-Posted on Tumblr, Fanwork Research & Reference Guides, Gender Related, Meta, Nonfiction, Television
Language: English
Status: Completed
Published: 2015-08-23
Updated: 2015-08-23
Packaged: 2019-09-13 09:58:45
Rating: General Audiences
Warnings: No Archive Warnings Apply
Chapters: 1
Words: 2,647
Publisher: archiveofourown.org
Story URL: https://archiveofourown.org/works/16890411
Author URL: https://archiveofourown.org/users/destinationtoast/pseuds/toastystats
Summary: A comparison of several methods for approximately measuring gender bias, and a look at representation in some recent television shows (as of 2015).





	[Fandom stats] Gender bias in television

**Author's Note:**

> Originally [posted on Tumblr](http://destinationtoast.tumblr.com/post/127453611589/toastystats-gender-bias-in-television-how-biased). I did not end up doing the promised follow ups between TV and TV fandom (due to difficulties getting enough data), but I did do an extensive follow up about [gender representation in movies vs. movie fandom](https://archiveofourown.org/works/14176743/chapters/32678409).

## TOASTYSTATS: GENDER BIAS IN TELEVISION

 **How biased is television in terms of gender representation?  How should we measure such bias?** There’s no one right way to measure this, but I’m going to take an exploratory look at what different metrics might tell us.  I’ll be looking at gender ratios in terms of number of cast members and number of total appearances.

Honestly, this post may get way further into the weeds than most people want to read -- it’s a lot of me thinking about how to measure bias.  If you don’t care about the details of measurement and are just interested in gender bias conclusions, **here’s the TL;DR:**

****

  * **Current popular U.S. TV is about 40% female** \-- very clearly biased in terms of gender representation -- according to a number of different possible ways of measuring.  The average is about the same for a number of metrics I looked at based on both number of cast members and number of appearances.
  * **The gender bias for the top-billed spot is even stronger: 30% female.**
  * **There are lots of TV shows that skew very male, but hardly any that skew very female.**



I’m doing this in part to prepare for a post comparing gender bias in TV to gender bias in TV fandoms and in shipping… **keep an eye out for more on representation and bias in fandom vs. TV soon.**  


For more detailed analysis and more data, as well as comparisons of lots of different ways of measuring bias, keep reading.

## Gender of characters in IMDB cast summary

Let’s start by look at the IMDB cast summaries for a bunch TV shows -- a list of the characters who appear in the most episodes.

 **30% of top scripted broadcast TV shows from 2012-13 have a woman listed first.**  (See notes at the end for how I chose these TV shows and gathered the data.)  I’m not sure how ties are broken when multiple characters appear in the same number of characters.

Here are the shows with a female top-listed spot from that year:

  * Grey’s Anatomy  

  * The Good Wife  

  * 2 Broke Girls  

  * Body of Proof  

  * Once Upon A Time  

  * Bones  

  * Revenge  

  * Scandal  

  * The Middle  




If we look at the full set of cast listed in the summaries, we can look at number of women vs. number of men and get the following view of the popular TV landscape:  


Shows above the orange line have more males than females in the IMDB summary cast.  From this, we can see that some TV shows are very heavily skewed toward mostly/all males in the top-billed cast; some have slightly more women than men, but none of these shows are heavily skewed toward females in the summary cast.  There are also a bunch of shows that have close to gender parity. **  
**

(The labels on this and the other graphs may be hard to read, but hopefully you can get a sense of the overall shape of the data.  The full data is available in a [spreadsheet](https://docs.google.com/spreadsheets/d/1ixHfnGyiFz7m5yOk3vNRCz5SiANuMUaondNKjmZ4OO0/edit#gid=1965677540).)

While it’s interesting and potentially useful to look at this in two dimensions, we can also reduce this data to the percentage of characters that are women for each show:

The horizontal axis now shows the percent of the summary cast that is female, and the vertical axis counts up the number of shows in each bucket.  Shows to the left of the orange line have a higher percentage of men than women in the IMDB summary cast.  The shows also get more female as you move downward in each stack.    


**The average popular TV show has a 40% female IMDB summary cast.**

I also looked at a larger set of TV shows (including shows with large fandoms and female-focused shows -- see my notes at the end for further explanation of how I chose the set of shows):  


What’s interesting to me is how many TV shows I think of as having good gender representation -- or at least prominent women characters -- that actually score pretty low by this metric.  E.g., Agent Carter, Veronica Mars, and Elementary all have less than 30% women.  

Here are the characters in the summary cast for a few TV shows, to give you a better sense of this metric:

  * **Supernatural:** Sam, Dean  

  * **Xena, Warrior Princess:**  Xena, Gabrielle  

  * **X-Files:** Scully, Mulder, Skinner  

  * **Elementary:** Sherlock, Joan, Gregson, Marcus Bell  

  * **Sherlock:** Sherlock, John, Lestrade, Mrs. Hudson, Molly, Mycroft, Moriarty, Anderson  

  * **Buffy:**  Buffy, Xander, Willow, Giles, Spike, Anya, Dawn, Angel  

  * **Once Upon A Time:**  Mary Margaret, Emma Swan, Regina Mills, David Nolan, Henry Mills, Mr. Gold, Belle, Captain Hook, Ruby, Granny, Leroy  

  * **Agent Carter:** Peggy Carter, Jarvis, Jack Thompson, Daniel Sousa, Howard Stark  

  * **Game of Thrones:** Tyrion, Cersei, Daenerys, Jon Snow, Sansa, Jorah, Arya, Jaime, Sam Tarly, Theon, Littlefinger, Bronn, Varys, Tywin, The Hound, Brienne, Pycelle, Joffrey, Catelyn, Bran, Barristan Selmy, Stannis, Edd Tollett, Missandei, Grenn, Podrick, Davos, Robb, Margaery, Hodor, Shae, Melisandre, Loras  




****

I don’t know who determines which characters end up in this list.  And for some shows, the summary cast doesn’t include some of the favorite/best-known characters -- e.g., for Supernatural, the summary cast includes only Sam and Dean Winchester.  And the number of characters included varies hugely, as we can see by looking at the number of men and women for the large set of TV shows:

Because of these factors, I also thought about other ways to count the number of important characters.    


## Gender of characters above cast elbow

I came up with the idea of looking for an elbow -- or a big gap in number of appearances that separates key characters from side characters --  in the cast list.  For more details, see the notes at the end.  

If we look at the number of men vs. women who appear above the elbow (setting a minimum of 5 characters), we get the following:

How biased is popular TV by this metric?   **The average popular TV show has a 41% female cast above the elbow.** (I excluded the other TV shows that weren’t in the top 30 to calculate this average; I’ll be looking at the averages for the other shows more in future posts.  But I included all the TV shows in the graph because I think it’s helpful to have more data points when trying to understand the metric.)  


These are the shows that changed the most in the rankings from the previous metric:  


There are places where this metric arguably captures more of the important recurring cast (e.g., Elementary, X-Files, Agent Carter), but it also misses some important characters from the summary cast for a really big ensemble cast like Game of Thrones.  What do you think?  


On the whole, I think the elbow metric is more principled than the summary cast.  But it can still be misleading in terms of gender representation.  Some of these roles are a lot bigger than others.  E.g., Xena has dropped a lot in the rankings here (from 100% female in the summary cast to less than 70%) -- but that undervalues the importance of Xena and Gabrielle in the show.

What if we instead look at how many episodes each character appears in?  This isn’t a perfect indicator of how important the character is or how many scenes they’re in, obviously, but it’s a start.

## Gender ratio of characters’ appearances (above elbow)

Adding up the number of episodes for characters above the elbow and breaking down by gender, we get the following:

How biased is popular TV by this metric?   **The average popular TV show has 39% female appearances for cast above the elbow.**

These are the shows that changed the most in the rankings from the previous metric:  


It looks like shows tend to be less female when you count appearances than when you count cast members (this is only trending toward significance, though -- one-tailed t-test: p = 0.0944).  This would indicate that women in the main cast usually play smaller roles than men.  


(Note:  there’s no reason not to do a similar comparison between number appearances and number of characters for the IMDB summary.  I just didn’t get around to doing it here.)  


## Gender ratio of characters’ appearances (top X cast)

In part because I’m going to be comparing to AO3 in my next analysis (where it’s easy to examine the top 10 characters), I also looked at appearances for the top 10 listed cast members on IMDB.  And to try to get a more comprehensive look, I also looked at top 25 cast’s appearances.  


**The average for popular TV shows is 40%.**  


**The average for popular TV shows is 40% here, as well.**  


The main thing I note from this set of graphs is that, while the average is the same, **more of the shows fall into the 40-50% bucket the more cast members we add in.**

Another way of saying this is that the mean stays surprisingly stable for all the appearance metrics (and also the cast metrics we looked at first), but the standard deviation decreases the more cast members are included in the analysis (roughly, how spread out the TV shows are along the horizontal axis).  Standard deviation is 0.17 for the top 5 cast (not pictured above); 0.14 for the cast above the elbow; 0.13 for the top 10; and 0.12 for the top 25 cast.

## Conclusions

  * Popular TV is very clearly biased in terms of gender representation, regardless of which of a number of metrics you use to measure it.  The mean for the metrics I used hovered around 40% female (rather than the ~50% you would expect if it there were no gender bias).  
  

  * The gender bias for the top-billed spot is even stronger -- only 30% of those spots are female for popular TV.  
  

  * There are lots of TV shows that skew very male, and some near parity, but hardly any that skew very female.  
  

  * While the average stayed about the same, individual shows sometimes moved around a lot in the rankings for different metrics.  The IMDB summary may work better for finding the important characters for large ensemble casts; the elbow method may work better for other shows.  
  

  * To get a good sense of representation, it’s probably better for most purposes to look at number of appearances rather than number of cast members.  It looks like this may reveal a stronger bias (meaning, women in the main cast may play smaller roles on average than men in the main cast), although the trend was not significant for this data set.  
  

  * The amount of variance in the gender bias decreases the more cast members are included in the analysis.



I’ll also end by noting that adding in popular TV fandoms to the mix helps better assess the metrics, but doesn’t necessarily help with the degree of bias -- in fact, in some ways, it might hurt (but not necessarily in the ways you’d expect).  I’ll be comparing fandom to TV in further posts, and talking about how all this influences (or doesn’t) shipping.  Look for those posts, coming soonish.

(I say soon _ish_ because this post, which was basically just supposed to be a side tangent, took a couple weeks. Oops. :) )

## Additional notes/FAQ

You can find all the data and basic graphs [here](https://docs.google.com/spreadsheets/d/1ixHfnGyiFz7m5yOk3vNRCz5SiANuMUaondNKjmZ4OO0/edit#gid=954609244); you can find more data about the shows’ fandoms as well [here](https://docs.google.com/spreadsheets/d/1m9EmhZFL-UaZqOr5mqwHFk1BXDfSPGWdPIpGJt2EoDY/edit#gid=1632488286).   And [here’s](https://docs.google.com/presentation/d/1sjZaPQr2YhpRwNGDfFCQkpDC5C-G5Chu4APAYk3cA1c/edit#slide=id.gb8dd8f9d3_0_150) where I labeled the graphs and made them pretty.  


**Why only look at gender?**  I wanted to look at representation much more broadly, but got overwhelmed (I’m just doing this for fun in my spare time).  So I’m starting with gender bias because character gender is easier for me to identify by looking at IMDB cast lists than ethnicity, sexual orientation, disability, or other dimensions.  But I hope that by finding good methods to quantify gender representation, I will also come up with methods that can be extended to look at other forms of bias.  I believe that some other forms of bias (race and disability, e.g.) are even more pronounced than gender bias, and I don’t mean to imply that gender bias is the only thing I am concerned about.

 **Why only M and F?**  I considered also looking at trans and non-binary characters, but there wasn’t enough relevant data in this data set to work with. :(  But there’s no reason one couldn’t do similar calculations on a larger and more inclusive set of TV shows and also look at representation of non-binary characters.

 **Why only TV?**  IMDB has information about TV shows that allows me to approximate the size of each character’s role -- I can look at how many episodes a character appears in.  (Number of scenes, amount of screen time, or lines of dialogue would be a better proxy for the size of a role, but I can’t easily get that data.)  

 **Why 2012-2013 for popular TV?**  This is a side effect of my starting out trying to look at TV fandoms -- I wanted to choose shows that were recent, but had been around long enough that I could look at whether a fandom had sprung up for each popular TV show and how quickly it was growing.  I’ll be talking more about that in future posts.

 **How exactly did you choose these TV shows?**  I’m using two sets of TV shows for these analyses:

  * The top 30 most viewed scripted broadcast TV shows in 2012-2013 (meaning -- no streaming TV or premium cable; no reality TV or sports) according to the Neilsen ratings (which I obtained from [Zap2It](http://tvbythenumbers.zap2it.com/2013/05/29/complete-list-of-2012-13-season-tv-show-viewership-sunday-night-football-tops-followed-by-ncis-the-big-bang-theory-ncis-los-angeles/184781/)).  I believe this only measures U.S. viewership and is therefore obviously very culturally biased.
  * 72 TV shows that I am looking at for my gender representation in TV & fandom analysis -- the top 30 above, plus the top 30 TV fandoms on AO3 right now, plus some additional TV fandoms that are female- or femslash-focused.  I used the [AO3 TV Shows](http://archiveofourown.org/media/TV%20Shows/fandoms) page to determine the top 30 TV fandoms, as of July 2015.  This is obviously biased toward AO3, which is not representative of all of fandom; I’ve discussed before some of the ways that [fandom differs on different platforms](http://destinationtoast.tumblr.com/stats#platforms).



**How did you count appearances?** Mostly I just went by the number of appearances listed in IMDB, but when I noticed that those included episodes that haven’t aired yet (e.g., Sherlock S4 appearances), or very short specials (e.g., the 7 minute Sherlock special, “Many Happy Returns”), I omitted those.  However, I did count all episodes that aired through 2015, not just those that had aired in 2013.

For most shows, I only counted named characters (“Cigarette Smoking Man” counted, but “Waiter” did not) and tried to only count humanoid characters with apparent gender (e.g., no dogs; no aliens where gender was not apparent).  I didn’t count characters unless they appeared at least 3 times for most shows, but for shows with very few episodes (Sherlock, Firefly, e.g.) I lowered that to 2 appearances.

 **Did you count actors or characters?** When a single actor plays multiple characters (e.g., Orphan Black), I counted each character separately, including looking at how many episodes each character is in.  When multiple actors play one character (e.g., Ruby in Supernatural), I mostly combined into a single character (but I didn’t count “Young X” appearances).  An exception is Doctor Who, because fandom seems to mostly tag the different Doctors as different characters.

 **How’d you find the elbow?** I sorted the characters by number of appearances and looked for the biggest gap in appearances (I set a minimum of 5 characters above the elbow, though, because I wanted to get more than just the two most prominent characters for a show like Supernatural).  When there was a tie, I went with the more inclusive threshold.

 **Can I use this (or your raw data) in my research?** Please do.  Just cite me, and let me know if you have questions.  


End file.
